November 26, 2018 — Medical imaging software company Arterys will demonstrate its wide-ranging suite of artificial intelligence (AI)-powered solutions that support fast, efficient and accurate analysis of medical images at the 2018 Radiological Society of North America (RSNA 2018) annual meeting, Nov. 25-30 in Chicago.

Driven by deep learning and cloud computation, the Arterys platform uses the power of the internet to enhance clinician workflow, streamlining and speeding analysis of breast, heart, liver and lung images to deliver improved patient outcomes for key workflows.

Arterys Cardio AIMR combines deep learning and cloud computing to automate analysis of cardiac magnetic resonance (MR) images. By eliminating many tedious, manual tasks, Arterys Cardio AI enables clinicians to quickly and easily identify, determine treatment for and track heart problems. It is the first and only commercial solution, according to the company, to offer deep learning-based semi-quantitative perfusion and quantitative delayed enhancement analysis.

Arterys Viewer is powered by AI to increase speed, efficiency and accuracy of reading medical images. Offering multimodal support, including for MRI, computed tomography (CT), X-ray and ultrasound images, Arterys Viewer is designed to deliver the best patient outcome by enabling clinicians to share images, collaborate and consult via a shared workspace.

Basic artificial intelligence is already incorporated into several premium echocardiography systems. This example is from the Philips Epiq, where the AI takes 3-D datasets and automatically identifies and segments the cardiac anatomy. It then extracts the best images for each of the standard echocardiogram views to eliminate variation between operators. The next generation echo AI software will pull in data from the electronic medical records and imaging data to offer suggested diagnoses.

Presenter delivers pitch at last year’s ACC Future Hub. This year during ACC.19, entrepreneurs will pitch software and hardware specific to cardiology in two categories– artificial intelligence and digitally enabled medical devices. (Image courtesy of ACC)